Reliable feature deployment is provided. Features are evaluated for their readiness to be graduated and features that are ready to be graduated are added to a graduation list. When features are added to the graduation list, evaluation of the features is discontinued, thereby reducing the performance and runtime costs associated with deploying features. Furthermore, engineers can consult the graduation list to identify features that are ready for graduation, thereby reducing the risk of premature flight graduation. Data associated with features is analyzed to map the features to corresponding flights. In this way, when an engineer identifies a feature for graduation, the engineer is able to identify the corresponding flight (or flights) from the mapping. Even when a feature is selected for graduation, the present systems provide additional safeguards to ensure that corresponding flights are not improperly or prematurely graduated, thereby preventing a subpar customer experience.
Legal claims defining the scope of protection, as filed with the USPTO.
3. The computer-implemented method of claim 2, wherein the at least one code stub is removed based on a ramp down policy.
4. The computer-implemented method of claim 3, wherein the ramp down policy specifies that at least a first code stub associated with the deployed code for the first subset of users be removed before at least a second code stub associated with the deployed code for the second subset of users.
5. The computer-implemented method of claim 1, wherein evaluating the performance of the enabled feature comprises evaluating runtime use of one or more resources associated with a cloud computing environment hosting the plurality of tenants.
6. The computer-implemented method of claim 1, wherein evaluating the performance of the enabled feature comprises collecting telemetry data regarding use of the enabled feature by the first subset of users and the second subset of users.
7. The computer-implemented method of claim 1, wherein determining that the feature is ready to be graduated further comprises determining that the enabled feature is available to all tenants of the plurality of tenants.
8. The computer-implemented method of claim 7, wherein the first subset of users and the second subset of users are associated with all tenants of the plurality of tenants.
9. The computer-implemented method of claim 7, wherein determining that the feature is ready to be graduated further comprises determining that the feature has not been edited for a period of time.
10. The computer-implemented method of claim 9, wherein the period of time is within a range of 1 day to 60 days.
11. The computer-implemented method of claim 1, wherein the at least one code stub is mapped to the performance of the enabled feature in a mapping table.
15. The system of claim 14, wherein the at least one code stub is removed based on a ramp down policy.
16. The system of claim 13, wherein evaluating the performance of the enabled feature comprises evaluating runtime use of one or more resources associated with a cloud computing environment hosting the plurality of tenants.
17. The system of claim 13, wherein evaluating the performance of the enabled feature comprises collecting telemetry data regarding use of the enable feature by the plurality of tenants.
20. The computer storage medium of claim 18, wherein the at least one code stub is removed based on a ramp down policy.
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June 16, 2020
May 16, 2023
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